ReviewBiophysical reviews2020
Dominant rule of community effect in synchronized beating behavior of cardiomyocyte networks.
Review in Biophysical reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- A Multi-Task Deep Learning Framework for Characterizing Beating Behavior and Synchrony in Cardiomyocyte Clusters.Bioengineering (Basel, Switzerland) · 2026Article
- Principles, mechanisms and functions of entrainment in biological oscillators.Interface focus · 2022Review
- In Situ Agarose Microfabrication Technology Using Joule Heating of Micro Ionic Current for On-Chip Cell Network Analysis.Micromachines · 2022Article
- Stepwise neuronal network pattern formation in agarose gel during cultivation using non-destructive microneedle photothermal microfabrication.Scientific reports · 2021Article
- Biophysical Reviews: 2020-looking back, going forward.Biophysical reviews · 2020Article
- Biophysical Reviews' national biophysical society partnership program.Biophysical reviews · 2020Article
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Authors and funding
1 author.
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Abstract
Exploiting the combination of latest microfabrication technologies and single cell measurement technologies, we can measure the interactions of single cells, and cell networks from "algebraic" and "geometric" perspectives under the full control of their environments and interactions. However, the experimental constructive single cell-based approach still remains the limitations regarding the quality and condition control of those cells. To overcome these limitations, mathematical modeling is one of the most powerful complementary approaches. In this review, we first explain our on-chip experimental methods for constructive approach, and we introduce the results of the "community effect" of beating cardiomyocyte networks as an example of this approach. On-chip analysis revealed that (1) synchronized interbeat intervals (IBIs) of cell networks were followed to the more stable beating cells even their IBIs were slower than the other cells, which is against the conventional faster firing regulation or "overdrive suppression," and (2) fluctuation of IBIs of cardiomyocyte networks decreased according to the increase of the number of connected cells regardless of their geometry. The mathematical simulation of this synchronous behavior of cardiomyocyte networks also fitted well with the experimental results after incorporating the fluctuation-dissipation theorem into the oscillating stochastic phase model, in which the concept of spatially arranged cardiomyocyte networks was involved. The constructive experiments and mathematical modeling indicated the dominant rule of synchronization behavior of beating cardiomyocyte networks is a kind of stability-oriented synchronization phenomenon as the "community effect" or a fluctuation-dissipation phenomenon. Finally, as a practical application of this approach, the predictive cardiotoxicity is introduced.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.